Computational study of the interplay between intermolecular interactions and CO2 orientations in type I hydrates

Carbon dioxide (CO2) molecules show a rich orientation landscape when they are enclathrated in type I hydrates. Previous studies have described experimentally their preferential orientations, and some theoretical works have explained, but only partially, these experimental results. In the present paper, we use classical molecular dynamics and electronic density functional theory to advance in the theoretical description of CO2 orientations within type I hydrates. Our results are fully compatible with those previously reported, both theoretical and experimental, the geometric shape of the cavities in hydrate being, and therefore, the steric constraints, responsible for some (but not all) preferential angles. In addition, our calculations also show that guest–guest interactions in neighbouring cages are a key factor to explain the remaining experimental angles. Besides the implication concerning equation of state hydrate modeling approximations, the conclusion is that these guest–guest interactions should not be neglected, contrary to the usual practice

DFT calculation of the potential energy landscape topology and Raman spectra of type I CH4 and CO2 hydrates

CO2 and CH4 clathrate hydrates of type I were studied by means of DFT and QTAIM, in order to better understand their properties at the molecular level. Sub-cells of type I hydrates were modeled as independent rigid cages, both empty and containing guest molecules. Interaction potentials of guest molecules inside each cage, and moving from a cell to the adjacent one, were calculated using the DFT approximation B3LYP/6-311+g(d,p), considering the cases with and without long range Coulombic corrections. The selected theory level was validated by comparison of the simulated Raman spectra with the experimental ones, for the case of type I lattice at full occupation of CO2 and CH4, respectively. For this comparison, Fermi resonances of CO2 were taken into account by transforming experimental bands to the corresponding theoretical non-mixed states. On the one hand, our results confirm the validity of the theory level selected for the model. We have shown the high anisotropy of the guest–cell interaction potential of the molecules analyzed, which has implications in the formulation and use of equations of state, and in the study of transport properties as well. On the other hand, our results suggest that the concentration of guest species inside type I hydrates could be computed from the comparison of experimental and predicted Raman spectra, although there are non-trivial experimental limitations to get over for that purpose

Hard Two-Photon Contribution to Elastic Lepton-Proton Scattering: Determined by the OLYMPUS Experiment

The OLYMPUS collaboration reports on a precision measurement of the positron-proton to electron-proton elastic cross section ratio, $R_{2\gamma}$, a direct measure of the contribution of hard two-photon exchange to the elastic cross section. In the OLYMPUS measurement, 2.01~GeV electron and positron beams were directed through a hydrogen gas target internal to the DORIS storage ring at DESY. A toroidal magnetic spectrometer instrumented with drift chambers and time-of-flight scintillators detected elastically scattered leptons in coincidence with recoiling protons over a scattering angle range of $\approx 20\degree$ to $80\degree$. The relative luminosity between the two beam species was monitored using tracking telescopes of interleaved GEM and MWPC detectors at $12\degree$, as well as symmetric M{\o}ller/Bhabha calorimeters at $1.29\degree$. A total integrated luminosity of 4.5~fb$^{-1}$ was collected. In the extraction of $R_{2\gamma}$, radiative effects were taken into account using a Monte Carlo generator to simulate the convolutions of internal bremsstrahlung with experiment-specific conditions such as detector acceptance and reconstruction efficiency. The resulting values of $R_{2\gamma}$, presented here for a wide range of virtual photon polarization $0.456<\epsilon<0.978$, are smaller than some hadronic two-photon exchange calculations predict, but are in reasonable agreement with a subtracted dispersion model and a phenomenological fit to the form factor data.Comment: 5 pages, 3 figures, 2 table

Worries about being judged versus being harmed: Disentangling the association of social anxiety and paranoia with schizotypy

Paranoia is a dimension of clinical and subclinical experiences in which others are believed to have harmful intentions. Mild paranoid concerns are relatively common in the general population, and more clinically severe paranoia shares features with social anxiety and is a key characteristic of schizotypy. Given that subclinical manifestations of schizotypy and paranoia may predict the occurrence of more severe symptoms, disentangling the associations of these related constructs may advance our understanding of their etiology; however no known studies to date have comprehensively evaluated how paranoia relates to social anxiety and schizotypy. The current research sought to examine the association of paranoia, assessed across a broad continuum of severity, with 1) the positive and negative schizotypy dimensions and 2) social anxiety. Specifically, the study tested a series of six competing, a priori models using confirmatory factor analysis in a sample of 862 young adults. As hypothesized, the data supported a four-factor model including positive schizotypy, negative schizotypy, social anxiety, and paranoia factors, suggesting that these are distinct constructs with differing patterns of interrelationships. Paranoia had a strong association with positive schizotypy, a moderate association with social anxiety, and a minimal association with negative schizotypy. The results are consistent with paranoia being part of a multidimensional model of schizotypy and schizophrenia. Prior studies treating schizotypy and schizophrenia as homogenous constructs often produce equivocal or non-replicable results because these dimensions are associated with distinct etiologies, presentations, and treatment responses; thus, the present conceptualization of paranoia within a multidimensional schizotypy framework should advance our understanding of these constructs. © 2014 Horton et al

Genetic architecture of brain age and its causal relations with brain and mental disorders

Abstract The difference between chronological age and the apparent age of the brain estimated from brain imaging data—the brain age gap (BAG)—is widely considered a general indicator of brain health. Converging evidence supports that BAG is sensitive to an array of genetic and nongenetic traits and diseases, yet few studies have examined the genetic architecture and its corresponding causal relationships with common brain disorders. Here, we estimate BAG using state-of-the-art neural networks trained on brain scans from 53,542 individuals (age range 3–95 years). A genome-wide association analysis across 28,104 individuals (40–84 years) from the UK Biobank revealed eight independent genomic regions significantly associated with BAG ( p < 5 × 10 −8 ) implicating neurological, metabolic, and immunological pathways – among which seven are novel. No significant genetic correlations or causal relationships with BAG were found for Parkinson’s disease, major depressive disorder, or schizophrenia, but two-sample Mendelian randomization indicated a causal influence of AD ( p = 7.9 × 10 −4 ) and bipolar disorder ( p = 1.35 × 10 −2 ) on BAG. These results emphasize the polygenic architecture of brain age and provide insights into the causal relationship between selected neurological and neuropsychiatric disorders and BAG

Constructing personalized characterizations of structural brain aberrations in patients with dementia using explainable artificial intelligence

Deep learning approaches for clinical predictions based on magnetic resonance imaging data have shown great promise as a translational technology for diagnosis and prognosis in neurological disorders, but its clinical impact has been limited. This is partially attributed to the opaqueness of deep learning models, causing insufficient understanding of what underlies their decisions. To overcome this, we trained convolutional neural networks on structural brain scans to differentiate dementia patients from healthy controls, and applied layerwise relevance propagation to procure individual-level explanations of the model predictions. Through extensive validations we demonstrate that deviations recognized by the model corroborate existing knowledge of structural brain aberrations in dementia. By employing the explainable dementia classifier in a longitudinal dataset of patients with mild cognitive impairment, we show that the spatially rich explanations complement the model prediction when forecasting transition to dementia and help characterize the biological manifestation of disease in the individual brain. Overall, our work exemplifies the clinical potential of explainable artificial intelligence in precision medicine

Rituximab, plasma exchange and immunoglobulins: an ineffective treatment for chronic active antibody-mediated rejection

BACKGROUND: Chronic active antibody-mediated rejection (c-aABMR) is an important cause of allograft failure and graft loss in long-term kidney transplants. METHODS: To determine the efficacy and safety of combined therapy with rituximab, plasma exchange (PE) and intravenous immunoglobulins (IVIG), a cohort of patients with transplant glomerulopathy (TG) that met criteria of active cABMR, according to BANFF'17 classification, was identified. RESULTS: We identified 62 patients with active c-aABMR and TG (cg ≥ 1). Twenty-three patients were treated with the combination therapy and, 39 patients did not receive treatment and were considered the control group. There were no significant differences in the graft survival between the two groups. The number of graft losses at 12 and 24 months and the decline of eGFR were not different and independent of the treatment. A decrease of eGFR≥13 ml/min between 6 months before and c-aABMR diagnosis, was an independent risk factor for graft loss at 24 months (OR = 5; P = 0.01). Infections that required hospitalization during the first year after c-aABMR diagnosis were significantly more frequent in treated patients (OR = 4.22; P = 0.013), with a ratio infection/patient-year of 0.65 and 0.20 respectively. CONCLUSIONS: Treatment with rituximab, PE, and IVIG in kidney transplants with c-aABMR did not improve graft survival and was associated with a significant increase in severe infectious complications

Cofactors facilitate bona fide prion misfolding in vitro but are not necessary for the infectivity of recombinant murine prions

Prion diseases, particularly sporadic cases, pose a challenge due to their complex nature and heterogeneity. The underlying mechanism of the spontaneous conversion from PrPC to PrPSc, the hallmark of prion diseases, remains elusive. To shed light on this process and the involvement of cofactors, we have developed an in vitro system that faithfully mimics spontaneous prion misfolding using minimal components. By employing this PMSA methodology and introducing an isoleucine residue at position 108 in mouse PrP, we successfully generated recombinant murine prion strains with distinct biochemical and biological properties. Our study aimed to explore the influence of a polyanionic cofactor in modulating strain selection and infectivity in de novo-generated synthetic prions. These results not only validate PMSA as a robust method for generating diverse bona fide recombinant prions but also emphasize the significance of cofactors in shaping specific prion conformers capable of crossing species barriers. Interestingly, once these conformers are established, our findings suggest that cofactors are not necessary for their infectivity. This research provides valuable insights into the propagation and maintenance of the pathobiological features of cross-species transmissible recombinant murine prion and highlights the intricate interplay between cofactors and prion strain characteristics.The present work was partially funded by three different grants awarded by “Agencia Estatal de Investigación, Ministerio de Ciencia e Innovación” (Spanish Government), grant numbers PID2021-122201OB-C21 granted to J.C., PID2021-1222010B-C22 granted to E.V., and PID2020-117465GB-I00 granted to J.R.R., funded by MCIN/ AEI /10.13039/501100011033 and co-financed by the European Regional Development Fund (ERDF). EFA031/01 NEURO-COOP, which is co-funded at 65% by the European Union through Programa Interreg VI-A España-Francia-Andorra (POCTEFA 2021-2027) granted to J.C. and H.E. Additional funding was provided by the Instituto de Salud Carlos III (ISCIII), grant number AC21_2/00024, granted to J.C. Additionally, CIC bioGUNE currently holds a Severo Ochoa Excellence accreditation, CEX2021-001136-S granted to J.C., also funded by Ministerio de Ciencia e Innovación/AEI /10.13039/501100011033. Transgenic Facility, directed by M.A.S.-M., is supported by Instituto de Salud Carlos III (ISCIII), co-funded by the European Union grant PT23/00123. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.info:eu-repo/semantics/publishedVersio